test

app.py

@@ -10,29 +10,6 @@ import os
 import requests
 import csv
 import spaces
-# from triton.fb import build_paths
-
-# from torch.utils.cpp_extension import load
-
-# # Compile and load the CUDA extension
-# adaptive_conv_cuda_impl = load(
-#     name='adaptive_conv_cuda_impl',
-#     sources=[
-#         'featup/adaptive_conv_cuda/adaptive_conv_cuda.cpp',
-#         'featup/adaptive_conv_cuda/adaptive_conv_kernel.cu'
-#     ],
-#     extra_cflags=['-O3'],
-#     extra_cuda_cflags=['-O3']
-# )
-
-# # Compile and load the C++ extension
-# adaptive_conv_cpp_impl = load(
-#     name='adaptive_conv_cpp_impl',
-#     sources=['featup/adaptive_conv_cuda/adaptive_conv.cpp'],
-#     extra_cflags=['-O3']
-# )
-
-# print(adaptive_conv_cuda_impl, adaptive_conv_cpp_impl)
 
 def plot_feats(image, lr, hr):
     from featup.util import pca, remove_axes
@@ -112,12 +89,9 @@ model_option = gr.Radio(options, value="dino16",
 
 @spaces.GPU
 def upsample_features(image, model_option):
-
-    output = subprocess.check_output(['ls', '/']).decode()
-    print(output)
-    print(torch.version.cuda)
-    cuda_version = subprocess.run(['nvcc', '--version'], stdout=subprocess.PIPE)
-    print(cuda_version.stdout.decode('utf-8'))
+    
+    subprocess.check_call(
+        ["pip", "install", "git+https://github.com/mhamilton723/FeatUp"])
 
     from featup.util import norm, unnorm
     models = {o: torch.hub.load("mhamilton723/FeatUp", o) for o in options}